The rising prevalence of youth depression underscores the need to identify modifiable factors for prevention and intervention. This study aims to investigate the protective role of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet on depressive symptoms in adolescents.

Participants were identified from the Adolescent Brain Cognitive Development study. Adherence to the MIND diet was measured by the Child Nutrition Assessment or the Block Kids Food Screener. Depressive symptoms were measured annually using the Child Behavior Checklist's depression subscale. We utilized regression analyses and cross-lagged panel modeling (CLPM) to examine longitudinal associations. Additional analyses adjusted for polygenic risk scores for depression, and changes in Body Mass Index (BMI) and waist-to-height ratio.

Of the 8459 children (52.3 % male; mean age 10.9 [SD, 0.6] years), 2338 (27.6 %) demonstrated high MIND diet adherence, while 2120 (25.1 %) showed low adherence. High adherence was prospectively associated with reduced depressive symptoms (adjusted β, -0.64, 95 % CI, -0.73 to -0.55; p < 0.001) and 46 % lower odds of clinically relevant depression (adjusted odds ratio, 0.54, 95 % CI, 0.39 to 0.75; p < 0.001) at two-year follow-up. CLPM analyses showed significant cross-lag paths from MIND diet scores to less depressive symptoms across three time points. These associations persisted independently of changes in BMI and waist-to-height ratios, and were not significantly moderated by genetic predisposition to depression.

Higher adherence to the MIND dietary pattern was longitudinally associated with decreased risk of depressive symptoms in adolescents. Promoting MIND diet may represent a promising strategy for depression prevention in adolescent populations.

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in individuals genetically similar to European reference panels (EUR-like; n = 16,400 to 1,074,629). Traits included clinical (e.g. major depressive disorder, alcohol use disorder) and subclinical measures (e.g. risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

Previous genome-wide association studies of depression have primarily focused on common variants, limiting our comprehensive understanding of the genetic architecture. In contrast, whole-exome sequencing can capture rare coding variants, helping to explore the phenotypic consequences of altering protein-coding genes. Here, we conducted a large-scale exome-wide association study on 296,199 participants from the UK Biobank, assessing their depressive symptom scores through the Patient Health Questionnaire-4. We identified 22 genes associated with depressive symptoms, including 6 newly discovered genes (TRIM27, UBD, SVOP, ADGRB2, IRF2BPL, and ANKRD12). Both ontology enrichment analysis and plasma proteomics association analysis consistently revealed that the identified genes were associated with immune responses. Furthermore, we identified associations between these genes and brain regions related to depression, such as anterior cingulate cortex and orbitofrontal cortex. Additionally, phenome-wide association analysis demonstrated that TRIM27 and UBD were associated with neuropsychiatric, cognitive, biochemistry, and inflammatory traits. Our findings offer new insights into the potential mechanisms and genetic architecture of depressive symptoms.

To investigate the impact of personality trait clusters on the quality of life (QoL) of breast cancer survivors (BCS) during the first 18 months following diagnosis.

A cohort of 476 newly diagnosed breast cancer patients was recruited between January 2017 and August 2018 from a single academic hospital in Seoul, Korea. Five-factor models of personality traits were assessed at baseline. QoL evaluations were performed prior to surgery and up to 18 months post-surgery. K-means clustering analysis was employed to construct personality clusters. Long-term QoL trajectories in BCS were compared between clusters, adjusting for individual resilience. Furthermore, a polygenic risk score (PRS) for neuroticism was calculated, exploring its relationships with neuroticism and personality trait clusters identified in this study.

Cluster analysis suggested that a two-cluster model was more appropriate than a three-cluster model. The two clusters were characterized by (1) low neuroticism and high scores in the other four traits, and (2) high neuroticism and low scores in the other four traits. Patients in cluster 2 exhibited significantly lower baseline QoL scores compared to those in other clusters, from baseline through 18 months post-surgery. The PRS for neuroticism showed a significant association with neuroticism scores (p = 0.032) after adjusting for age and depression scores. No significant differences in PRS were observed between the clusters. Additionally, the PRS for neuroticism was not significantly associated with QoL.

Our findings underscore the influence of individual personality traits on long-term QoL in BCS. These results suggest the potential for targeted interventions to enhance long-term QoL based on personalized personality profiles.

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD). A latent class analysis (LCA) was performed on 22,668 individuals from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic overlap of psychiatric and psychosocial traits in 7659 individuals of European descent and epigenome-wide changes in 886 individuals of African, European, and Admixed-American descents. The LCA identified four latent classes related to SD comorbidities: AD + TD, CoD + TD, AD + CoD + OD + TD (i.e., polysubstance addiction, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD + TD, AD + TD, and PSU latent classes. AD + TD latent class was also associated with CpG sites located on ARID1B, NOTCH1, SERTAD4, and SIN3B, while additional epigenome-wide significant associations with CoD + TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1. We also observed shared polygenic score (PGS) associations for PSU, AD + TD, and CoD + TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD + TD-latent class (bipolar disorder-PGS). In conclusion, we identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Subjective well-being (SWB) is important for understanding human behaviour and health. Although the connection between SWB and psychiatric disorders has been studied, common genetic mechanisms remain unclear. This study aimed to explore the genetic relationship between SWB and psychiatric disorders. Bivariate causal mixture modelling (MiXeR), polygenic risk score (PRS) and Mendelian randomization (MR) analyses showed substantial polygenic overlap and associations between SWB and the psychiatric disorders. Subsequent replication studies in East Asian populations confirmed the polygenic overlap between schizophrenia and SWB. The conditional and conjunctional false discovery rate analyses identified additional or shared genetic loci associated with SWB or psychiatric disorders. Functional annotation revealed enrichment of specific brain tissues and genes associated with SWB. The identified genetic loci showed cross-ancestry transferability between the European and Korean populations. Our findings provide valuable insights into the common genetic mechanisms underlying SWB and psychiatric disorders.

Non-coding variants discovered by genome-wide association studies (GWASs) are enriched in regulatory elements harboring transcription factor (TF) binding motifs, strongly suggesting a connection between disease association and the disruption of cis-regulatory sequences. Occupancy of a TF inside a region of open chromatin can be detected in ATAC-seq where bound TFs block the transposase Tn5, leaving a pattern of relatively depleted Tn5 insertions known as a "footprint." Here, we sought to identify variants associated with TF binding, or "footprint quantitative trait loci" (fpQTLs), in ATAC-seq data generated from 170 human liver samples. We used computational tools to scan the ATAC-seq reads to quantify TF binding likelihood as "footprint scores" at variants derived from whole-genome sequencing generated in the same samples. We tested for association between genotype and footprint score and observed 809 fpQTLs associated with footprint-inferred TF binding (FDR < 5%). Given that Tn5 insertion sites are measured with base-pair resolution, we show that fpQTLs can aid GWAS and QTL fine-mapping by precisely pinpointing TF activity within broad trait-associated loci where the underlying causal variant is unknown. Liver fpQTLs were strongly enriched across ChIP-seq peaks, liver expression QTLs (eQTLs), and liver-related GWAS loci, and their inferred effect on TF binding was concordant with their effect on underlying sequence motifs in 78% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding-site disruption in complex traits, and provide functional insights into non-coding variants, ultimately informing novel treatments for common diseases.

Previous studies have shown that neuroticism and artificially sweetened food all play essential roles in chronic pain to varying degrees. However, it is unclear precisely the causal relationship between neuroticism traits and chronic pain and whether an unhealthy sweetened food is a mediator in this process.

This study employed rigorous research methods to ensure the validity of the findings. We utilized Mendelian randomization (MR) to examine the causal relationships between neuroticism traits, artificially sweetened food, and chronic pain. The data encompass four neuroticism traits (neuroticism, experiencing mood swings, depressed affect, and worry), consumption levels of nine artificially sweetened foods, and seven types of chronic pain. The primary statistical method employed was inverse variance weighting (IVW). Eventually, we explored whether artificially sweetened food serves as a mediator in the relationship between neuroticism traits and chronic pain.

We found that genetic predisposition to higher neuroticism traits and the consumption of artificial sweeteners is associated with an increased risk of chronic pain across multiple sites. Reverse MR analysis also confirms that chronic pain at multiple sites similarly increases the risk of neuroticism traits. Two-step MR suggests the mediating effects of five artificial sweeteners on sciatica: low back pain, thoracic pain, low back pain, joint pain, and muscular pain. These findings could inform interventions and treatments for chronic pain.

Neuroticism traits and chronic pain have causal relationships, with artificially sweetened food mediating the pathway from neuroticism traits to chronic pain.

Bipolar disorder (BD) and major depressive disorder (MDD) aggregate within families, with risk often first manifesting as early psychopathology, including attention-deficit/hyperactivity disorder (ADHD) and anxiety disorders.

To determine whether polygenic scores (PGS) are associated with mood disorder onset independent of familial high risk for BD (FHR-BD) and early psychopathology.

This cohort study used data from 7 prospective cohorts enriched in FHR-BD from Australia, Canada, the Netherlands, Spain, and the US. Participants with FHR-BD, defined as having at least 1 first-degree relative with BD, were compared with participants without FHR for any mood disorder. Participants were repeatedly assessed with variable follow-up intervals from July 1992 to July 2023. Data were analyzed from August 2023 to August 2024.

PGS indexed genetic liability for MDD, BD, anxiety, neuroticism, subjective well-being, ADHD, self-regulation, and addiction risk factor. Semistructured diagnostic interviews with relatives established FHR-BD. ADHD or anxiety disorder diagnoses before mood disorder onset constituted early psychopathology.

The outcome of interest, mood disorder onset, was defined as a consensus-confirmed new diagnosis of MDD or BD. Cox regression examined associations of PGS, FHR-BD, ADHD, and anxiety with mood disorder onset. Kaplan-Meier curves and log-rank tests evaluated the probability of onset by PGS quartile and familial risk status.

A total of 1064 participants (546 [51.3%] female; mean [SD] age at last assessment, 21.7 [5.1] years), including 660 with FHR-BD and 404 without FHR for any mood disorder, were repeatedly assessed for mental disorders. A total of 399 mood disorder onsets occurred over a variable mean (SD) follow-up interval of 6.3 (5.7) years. Multiple PGS were associated with onset after correcting for FHR-BD and early psychopathology, including PGS for ADHD (hazard ratio [HR], 1.19; 95% CI, 1.06-1.34), self-regulation (HR, 1.19; 95% CI, 1.06-1.34), neuroticism (HR, 1.18; 95% CI, 1.06-1.32), MDD (HR, 1.17; 95% CI, 1.04-1.31), addiction risk factor (HR, 1.16; 95% CI, 1.04-1.30), anxiety (HR, 1.15; 95% CI, 1.02-1.28), BD (HR, 1.14; 95% CI, 1.02-1.28), and subjective well-being (HR, 0.89; 95% CI, 0.79-0.99). High PGS for addiction risk factor, anxiety, BD, and MDD were associated with increased probability of onset in the control group. High PGS for ADHD and self-regulation increased rates of onset among participants with FHR-BD. PGS for self-regulation, ADHD, and addiction risk factors showed stronger associations with onsets of BD than MDD.

In this cohort study, multiple PGS were associated with mood disorder onset independent of family history of BD and premorbid diagnoses of ADHD or anxiety. The association between PGS and mood disorder risk varied depending on family history status.

The frequent co-occurrence of chronic pain (CP) and depression is a well-known phenomenon, supported by both the high prevalence of major depression among CP patients and studies describing a substantial genetic correlation between the two phenotypes. Neuroticism, a trait characterised by maladaptive stress responses and a tendency to experience negative emotions, has been linked to both depression and the experience of pain. This study aimed to determine whether depression associated with CP represents a genetically distinct subtype and to explore the role of neuroticism in modulating genetic susceptibility to depression. To address these questions, we performed genome-wide association analyses for current depression utilising the UK Biobank dataset, followed by genome-wide by trait interaction analyses to assess the interaction effect of neuroticism, and polygenic risk score analyses to compare predictions. Our findings suggest that CP-related depression is a valid subtype of depression. In association with current depression, we identified a total of 49 novel genetic risk polymorphisms meeting the genome-wide significance threshold, including variants involved in synaptic plasticity and transcriptional regulation. Additionally, our results support that neuroticism has a prominent role in modulating the genetic risk of current depression independently of CP, which highlights the importance of considering personality traits and stress factors in understanding the genetic background of complex and heterogeneous phenotypes like depression.

The occurrence of urinary tract or kidney infection is correlated with intelligence, noncognitive education and cognition, but the causal relationship between them remains uncertain, and which risk factors mediate this causal relationship remains unknown.

The intelligence (n=269,867), noncognitive education (n=510,795) and cognition data (n=257,700) were obtained from genome-wide association studies (GWAS) conducted in individuals of European ethnicities. The genetic associations between these factors and urinary tract or kidney infection (UK Biobank, n=397,867) were analyzed using linkage disequilibrium score regression. We employed a two-sample univariate and multivariate Mendelian randomization to evaluate the causal relationship, and utilized a two-step Mendelian randomization to examine the involvement of 28 potential mediators and their respective mediating proportions.

The genetic correlation coefficients of intelligence, noncognitive education, cognition, and urinary tract or kidney infection were -0.338, -0.218, and -0.330. The Mendelian randomization using the inverse variance weighted method revealed each 1-SD increase in intelligence, the risk of infection decreased by 15.9%, while after adjusting for noncognitive education, the risk decreased by 20%. For each 1-SD increase in noncognitive education, the risk of infection decreased by 8%, which further reduced to 7.1% after adjusting for intelligence and to 6.7% after adjusting for cognition. For each 1-SD increase in cognition, the risk of infection decreased by 10.8%, increasing to 11.9% after adjusting for noncognitive education. The effects of intelligence and cognition are interdependent. 2 out of 28 potential mediating factors exhibited significant mediation effects in the causal relationship between noncognitive education and urinary tract or kidney infection, with body mass index accounting for 12.1% of the mediation effect and smoking initiation accounting for 14.7%.

Enhancing intelligence, noncognitive education, and cognition can mitigate the susceptibility to urinary tract or kidney infection. Noncognitive education exhibited independent effect, while body mass index and smoking initiation assuming a mediating role.

Previous observational studies showed associations between obstructive sleep apnea (OSA) and depression and other negative moods. However, the causality has not been determined. Single nucleotide polymorphisms were identified as instrumental variables by screening from genome-wide association studies. Bidirectional two-sample mendelian randomization (MR) was applied to assess the potential causal relationship between OSA and depression, subjective well-being, negative moods. Inverse variance weighting (IVW) method and weight median were chosen as the main methods to estimate possible causal effects. MR-Egger, MR pleiotropy residual sum and outlier and leave-one-out analysis methods, were used as sensitivity analysis methods to ensure robust results. MR analyses indicated significantly causal association of OSA on depression (OR = 1.22, P = .010) and major depressive disorder (OR = 1.02, P = .006). Furthermore, genetically predicted OSA was negatively associated with subjective well-being (βIVW = -0.06, P = .009), and was positively associated with negative moods including depressed affect (OR = 1.04, P = .012), irritable mood (P = .006), feeling lonely (P = .011), feeling fed-up (P = .005) and mood swings (P = .017). There is no reverse effect of the above psychiatric traits on OSA. Genetic predisposition to OSA causally increased depression and major depressive disorder. Consistently, OSA has causal impacts on both subjective well-being, representing positive emotions, and negative moods.

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable burdens. The etiological factors contributing to TRD are complex and not fully understood.

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits and explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us (AoU) Research Program.

This study was a cohort design with observational data from participants in the AoU Research Program who have both electronic health records and genomic data. Data analysis was performed from March 27 to October 24, 2024.

PGS for 61 unique traits from 7 domains.

Logistic regressions to test if PGS was associated with treatment-resistant depression (TRD) compared with treatment-responsive major depressive disorder (trMDD). Cox proportional hazard model was used to determine if the progressions from MDD to TRD were associated with PGS.

A total of 292 663 participants (median [IQR] age, 57 (41-69) years; 175 981 female [60.1%]) from the AoU Research Program were included in this analysis. In the discovery set (124 945 participants), 11 of the selected PGS were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia (odds ratio [OR], 1.11; 95% CI, 1.07-1.15) and specific neuroticism (OR, 1.11; 95% CI, 1.07-1.16) traits were associated with increased TRD risk, whereas higher education (OR, 0.88; 95% CI, 0.85-0.91) and intelligence (OR, 0.91; 95% CI, 0.88-0.94) scores were protective. The associations held across different TRD definitions (meta-analytic R2 >83%) and were consistent across 2 other independent sets within AoU (the whole-genome sequencing Diversity dataset, 104 388, and Microarray dataset, 63 330). Among 28 964 individuals followed up over time, 3854 developed TRD within a mean of 944 days (95% CI, 883-992 days). All 11 previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD.

Results of this cohort study suggest that genetic predisposition related to neuroticism, cognitive function, and sleep patterns had a significant association with the development of TRD. These findings underscore the importance of considering psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance understanding of pathways leading to treatment resistance.

A longed lack of control over harmful stimuli can lead to learned helplessness (LH), a significant factor in depression. However, the cellular and molecular mechanisms underlying LH, and eventually behavioral despair, remain largely unknown. The deleted in colorectal cancer (dcc) gene is associated with the risk of depression. However, the therapeutic potential and regulation mechanism of DCC in behavioral despair are still uncertain. In this study, we showed that depressive stimulators, including LH, lipopolysaccharide, and unpredictable chronic mild stress, triggered an elevation in DCC expression in the medial prefrontal cortex (mPFC). Additionally, elevated DCC expression in the mPFC was crucial in inducing behavioral despair, as evidenced by the induction of behavioral despair in normal mice and exacerbation of behavioral despair in LH mice upon DCC overexpression. By contrast, neutralizing DCC activity ameliorated LH-induced behavioral despair. Importantly, we elucidated that pathological DCC expression was attributable to the excessive excitation of CaMKII+ neurons in a manner dependent on the calpain-mediated degradation of SCOP and aberrant phosphorylation of the ERK signaling pathway. In addition, the increase in DCC expression led to a decreased excitability threshold in CaMKII+ neurons in the mPFC, which was supported by the observation that the ligand netrin 1 increased the frequency of action potential firing and of spontaneous excitatory postsynaptic currents in CaMKII+ neurons. In conclusion, our data indicate that LH triggers the excessive excitation of CaMKII+ neurons and activation of calpain-SCOP/ERK signaling to promote DCC expression, and DCC represents a crucial target for the treatment of LH-induced behavioral despair in male mice.

Income is associated with many health outcomes, but it is unclear how far this reflects a causal relationship. Mendelian randomisation (MR) uses genetic variation between individuals to investigate causal effects and may overcome some of the confounding issues inherent in many observational study designs.

We used two-sample MR using data from unrelated individuals to estimate the effect of log occupational income on indicators of mental health, physical health, and health-related behaviours. We investigated pleiotropy (direct effects of genotype on the outcome) using robust MR estimators, CAUSE, and multivariable MR including education as a co-exposure. We also investigated demographic factors and dynastic effects using within-family analyses, and misspecification of the primary phenotype using bidirectional MR and Steiger filtering.

We found that a 10% increase in income lowered the odds of depression (OR 0.92 [95% CI 0.86-0.98]), death (0.91 [0.86-0.96]), and ever-smoking (OR 0.91 [0.86-0.96]), and reduced BMI (- 0.06 SD [- 0.11, - 0.003]). We found little evidence of an effect on alcohol consumption (- 0.02 SD [- 0.01, 0.05]) or subjective wellbeing (0.02 SD [- 0.003, 0.04]), or on two negative control outcomes, childhood asthma (OR 0.99 [0.87, 1.13]) and birth weight (- 0.02 SD, [- 0.01, 0.05]). Within-family analysis and multivariable MR including education and income were imprecise, and there was substantial overlap between the genotypes associated with income and education: out of 36 genetic variants significantly associated with income, 29 were also significantly associated with education.

MR evidence provides some limited support for causal effects of income on some mental health outcomes and health behaviours, but the lack of reliable evidence from approaches accounting for family-level confounding and potential pleiotropic effects of education places considerable caveats on this conclusion. MR may nevertheless be a useful complement to other observational study designs since its assumptions and limitations are radically different. Further research is needed using larger family-based genetic cohorts, and investigating the overlap between income and other socioeconomic measures.

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in European-ancestry individuals (n = 16,400 to 1,074,629). Traits included clinical (e.g., major depressive disorder, alcohol use disorder) and subclinical measures (e.g., risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

An increasing number of observational studies have reported associations between frailty and mental disorders, but the causality remains ambiguous.

To assess the bidirectional causal relationship between frailty and nine mental disorders.

We conducted a bidirectional two-sample Mendelian randomisation on genome-wide association study summary data, to investigate causality between frailty and nine mental disorders. Causal effects were primarily estimated using inverse variance weighted method. Several secondary analyses were applied to verify the results. Cochran's Q-test and Mendelian randomisation Egger intercept were applied to evaluate heterogeneity and pleiotropy.

Genetically determined frailty was significantly associated with increased risk of major depressive disorder (MDD) (odds ratio 1.86, 95% CI 1.36-2.53, P = 8.1 × 10-5), anxiety (odds ratio 2.76, 95% CI 1.56-4.90, P = 5.0 × 10-4), post-traumatic stress disorder (PTSD) (odds ratio 2.56, 95% CI 1.69-3.87, P = 9.9 × 10-6), neuroticism (β = 0.25, 95% CI 0.11-0.38, P = 3.3 × 10-4) and insomnia (β = 0.50, 95% CI 0.25-0.75, P = 1.1 × 10-4). Conversely, genetic liability to MDD, neuroticism, insomnia and suicide attempt significantly increased risk of frailty (MDD: β = 0.071, 95% CI 0.033-0.110, P = 2.8 × 10-4; neuroticism: β = 0.269, 95% CI 0.173-0.365, P = 3.4 × 10-8; insomnia: β = 0.160, 95% CI 0.141-0.179, P = 3.2 × 10-61; suicide attempt: β = 0.056, 95% CI 0.029-0.084, P = 3.4 × 10-5). There was a suggestive detrimental association of frailty on suicide attempt and an inverse relationship of subjective well-being on frailty.

Our findings show bidirectional causal associations between frailty and MDD, insomnia and neuroticism. Additionally, higher frailty levels are associated with anxiety and PTSD, and suicide attempts are correlated with increased frailty. Understanding these associations is crucial for the effective management of frailty and improvement of mental disorders.

A core question in both human genetics and medicine is whether clinical disorders represent extreme manifestations of continuous traits or categorically distinct entities with unique genetic etiologies. To address this question, we introduce Genomic Taxometric Analysis of Continuous and Case-Control data (GTACCC), a novel method for systematically evaluating continuity and differentiation of traits across the severity spectrum. GTACCC's key innovation lies in binarizing continuous data at multiple severity thresholds, enabling the estimation of genetic continuity and differentiation within the trait and in its relation to other traits via multivariate models. We apply GTACCC to self-reported neuroticism data from UK Biobank (N= 414,448) and clinically ascertained major depressive disorder (MDD) data from the Psychiatric Genomics Consortium ( Σ N e f f = 111,221 ). We find that while neuroticism shares a considerable portion of its genetic etiology with MDD across the nonclinical, and even very low, range of (r g ∼ . 50 ), genetic sharing increases monotonically across the severity spectrum, approaching unity only at the highest levels of severity (r g ∼ 1.0 ). Genomic structural equation models indicate that a single liability threshold model of negative emotionality is less consistent with the data than a multifactor model, suggesting that a gradient of genetic differentiation emerges across the spectrum of negative emotionality. Thus, within continuous measures of negative emotionality, partly distinct genetic liabilities exist at varying severity levels, with only the most severe levels associated with liabilities that approach equivalence to MDD genetics.

Existing genetic studies of neuroticism have been largely limited to common variants. Here we performed a large-scale exome analysis of white British individuals from UK Biobank, revealing the role of coding variants in neuroticism. For rare variants, collapsing analysis uncovered 14 neuroticism-associated genes. Among these, 12 (PTPRE, BCL10, TRIM32, ANKRD12, ADGRB2, MON2, HIF1A, ITGB2, STK39, CAPNS2, OGFOD1 and KDM4B) were novel, and the remaining (MADD and TRPC4AP) showed convergent evidence with common variants. Heritability of rare coding variants was estimated to be up to 7.3% for neuroticism. For common variants, we identified 78 significant associations, implicating 6 unreported genes. We subsequently replicated these variants using meta-analysis across other four ancestries from UK Biobank and summary data from 23andMe sample. Furthermore, these variants had widespread impacts on neuropsychiatric disorders, cognitive abilities and brain structure. Our findings deepen the understanding of neuroticism's genetic architecture and provide potential targets for future mechanistic research.

While some studies have started to focus on the link between psychological well-being and age-related macular degeneration (AMD), the relationship remains uncertain. Our research aims to provide new insights into this association, laying a foundation for future interventions and addressing existing knowledge gaps.

We utilized the "TwoSampleMR" package in R for a bidirectional Mendelian randomization analysis of psychological well-being (subjective well-being, depression, neuroticism, and Sensitivity to Environmental Stress and Adversity) and early-stage AMD. Causal effects were estimated using the inverse-variance weighted method, and additional methods included weighted median and MR-Egger regression. Sensitivity analyses included Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO, and leave-one-out analysis.

The study found that the population with genetic predisposition to neuroticism had a 39.7% lower risk of early-stage AMD (OR = 0.603, 95% CI = 0.385-0.945, p = 0.027). Conversely, the population with genetic predisposition to subjective well-being had a 3.2% increased risk of early-stage AMD (OR = 1.032, 95% CI = 1.003-1.063, p = 0.029). No significant causal relationships were found from depression or Sensitivity to Environmental Stress and Adversity to early-stage AMD, nor from early-stage AMD to psychological well-being.

This study provides preliminary evidence that the relationship between psychological well-being and early-stage AMD may be complex and multifaceted. It suggests that moderate neuroticism levels might reduce early-stage AMD risk through health behaviors, pathophysiological mechanisms, and other factors, while high subjective well-being levels might increase this risk similarly. However, these findings are insufficient for preventive strategies due to a lack of substantial evidence and still require extensive experimental research for further validation.

Physical activities are widely implemented for non-pharmacological intervention to alleviate depressive symptoms. However, there is little evidence supporting their genotype-specific effectiveness in reducing the risk of self-harm in patients with depression.

To assess the associations between physical activity and self-harm behaviour and determine the recommended level of physical activity across the genotypes.

We developed the bidirectional analytical model to investigate the genotype-specific effectiveness on UK Biobank. After the genetic stratification of the depression phenotype cohort using hierarchical clustering, multivariable logistic regression models and Cox proportional hazards models were built to investigate the associations between physical activity and the risk of self-harm behaviour.

A total of 28 923 subjects with depression phenotypes were included in the study. In retrospective cohort analysis, the moderate and highly active groups were at lower risk of self-harm behaviour. In the followed prospective cohort analysis, light-intensity physical activity was associated with a lower risk of hospitalisations due to self-harm behaviour in one genetic cluster (adjusted hazard ratio, 0.28 [95% CI, 0.08-0.96]), which was distinguished by three genetic variants: rs1432639, rs4543289 and rs11209948. Compliance with the guideline-level moderate-to-vigorous physical activities was not significantly related to the risk of self-harm behaviour.

A genotype-specific dose of light-intensity physical activity reduces the risk of self-harm by around a fourth in depressive patients.

Humans exhibit distinct characteristics compared to our primate and ancient hominin ancestors. To investigate genomic bursts in the evolution of these traits, we use two complementary approaches to examine enrichment among genome-wide association study loci spanning diseases and AI-based image-derived brain, heart, and skeletal tissue phenotypes with genomic regions reflecting four evolutionary divergence points. These regions cover epigenetic differences among humans and rhesus macaques, human accelerated regions (HARs), ancient selective sweeps, and Neanderthal-introgressed alleles. Skeletal traits such as pelvic width and limb proportions showed enrichment in evolutionary annotations that mirror morphological changes in the primate fossil record. Additionally, we observe enrichment of loci associated with the longitudinal fasciculus in human-gained epigenetic elements since macaques, the visual cortex in HARs, and the thalamus proper in Neanderthal-introgressed alleles, implying that associated cognitive functions such as language processing, decision-making, sensory signaling, and motor control are enriched at different evolutionary depths.

The Internet is increasingly important in addressing age-related mental health challenges. We used linear mixed models and meta-analyses to examine the association between Internet use and mental health among 87,559 adults aged ≥50 years from 23 countries. Internet use was associated with fewer depressive symptoms (pooled average marginal effect (AME), -0.09; 95% confidence interval (CI), -0.12 to -0.07), higher life satisfaction (pooled AME, 0.07; 95% CI, 0.05 to 0.10) and better self-reported health (pooled AME, 0.15; 95% CI, 0.12 to 0.17). For two countries (the USA and England) with genetic data available, positive associations between Internet use and mental health were observed across three genetic risk categories. For three countries (the USA, England and China), a higher frequency of Internet use was related to better mental health. Our findings are relevant to public health policies and practices in promoting mental health in later life through the Internet, especially in countries with limited Internet access and mental health services.

Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants (25,255 non-responders and 110,216 responders). We performed genome-wide association meta-analyses, genetic correlation analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified two novel loci (rs1106260 and rs60847828) associated with non-response to antidepressants and showed significant polygenic prediction in independent samples. Genetic correlation analyses show positive associations between non-response to antidepressants and most psychiatric traits, and negative associations with cognitive traits and subjective well-being. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.

This study utilized the Mendelian randomization (MR) method to elucidate the causal relationship between genetically predicted overweight and various degrees of obesity with depressive symptoms and subjective well-being (SWB).

Pooled genome-wide association studies (GWAS) data for overweight (BMI ≥ 25 kg/m2), class 1 obesity (BMI ≥ 30 kg/m2), and class 2 obesity (BMI ≥ 35 kg/m2) were used as exposures. Summary GWAS data for depressive symptoms and SWB were used as outcomes. Multiple MR methods, primarily inverse-variance weighted (IVW), were applied, and sensitivity analyses were conducted to assess heterogeneity and pleiotropy.

The MR analysis provided evidence that genetically predicted overweight(IVW β = 0.033; 95 %CI 0.008-0.057; P = 0.010) and class 1 obesity(IVW β = -0.033; 95 %CI -0.047 - -0.020; P < 0.001) were causally associated with increased depressive symptoms. Genetically predicted class 2 obesity(IVW β = 1.428; 95 %CI 1.193-1.710; P < 0.001) were associated with reduced SWB. There was no strong evidence of a causal association between genetically predicted overweight and class 1 obesity with SWB. Similarly, genetically predicted class 2 and class 3 obesity did not show strong evidence of a causal association with depressive symptoms. Sensitivity analysis revealed relationships of a similar magnitude.

This genetically informed MR study suggests that Overweight and class 1 obesity may causally increased depressive symptoms but not decrease SWB. In contrast, class 2 obesity may causally decrease SWB but not increase depressive symptoms.

The day has arrived that genetic tests for educational outcomes are available to the public. Today parents and students alike can send off a sample of blood or saliva and receive a 'genetic report' for a range of characteristics relevant to education, including intelligence, math ability, reading ability, and educational attainment. DTC availability is compounded by a growing "precision education" initiative, which proposes the application of DNA tests in schools to tailor educational curricula to children's genomic profiles. Here I argue that these happenings are a strong signal of the geneticization of education; the process by which educational abilities and outcomes come to be examined, understood, explained, and treated as primarily genetic characteristics. I clarify what it means to geneticize education, highlight the nature and limitations of the underlying science, explore both real and potential downstream bioethical implications, and make proposals for mitigating negative impacts.

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Here, utilizing the Million Veteran Program cohort, we conducted a genome-wide association study in individuals of European and African ancestry. Adding other published data, we performed genome-wide association study meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 208, 14, 3, 2 and 7 independent genome-wide significant loci associated with neuroticism, extraversion, agreeableness, conscientiousness and openness, respectively. These findings represent 62 novel loci for neuroticism, as well as the first genome-wide significant loci discovered for agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety, while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

Genome-wide association studies (GWAS) and polygenic score (PGS) development are typically constrained by the data available in biobank repositories in which European cohorts are vastly overrepresented. Here, we increase the utility of non-European participant data within the UK Biobank (UKB) by characterizing the genetic affinities of UKB participants who self-identify as Bangladeshi, Indian, Pakistani, "White and Asian" (WA), and "Any Other Asian" (AOA), towards creating a more robust South Asian sample size for future genetic analyses. We assess the relationships between genetic structure and self-selected ethnic identities resulting in consistent patterns of clustering used to train a support vector machine (SVM). The SVM model was utilized to reassign n = 1,853 AOA and WA participants at the subcontinental level, and increase the sample size of the UKB South Asian group by 1,381 additional participants. We then leverage these samples to assess GWAS performance and PGS development. We further include environmental covariates in the height GWAS by implementing a rigorous covariate selection procedure, and compare the outputs of two GWAS models: GWASnull and GWASenv. We show that PGS performance derived from environmentally adjusted GWAS yields comparable prediction to PGS models developed with an order of magnitude larger training dataset (R 2=0.021 vs 0.026). Models with 7 - 8 environmental covariates double the variance explained by PGS alone. In summary, we demonstrate how GWAS performance can be improved by leveraging ambiguous ethnicity codes, ancestry matched imputation panels, and including environmental covariates.

Observational studies have indicated that breakfast skipping and gut microbiome dysbiosis are associated with a higher risk of major depressive disorder (MDD). However, it remains unknown whether the alteration of gut microbes is implicated in the associations between breakfast skipping and MDD.

Leveraging genome-wide association studies (GWAS) on breakfast skipping, gut microbes, and MDD, we conducted a two-step Mendelian randomization (MR) study to determine the causal associations between breakfast skipping (N = 193,860) and MDD (N = 1,815,091), and evaluate the role of gut microbes (N = 18,340). Genetic variants with a P-value less than 5E-08 were selected as instrumental variables (IVs). The false discovery rate (FDR) method was employed to correct the P-values for multiple tests in gut microbes.

Breakfast skipping was associated with an increased risk of MDD (odds ratio [OR] = 1.36, 95%CI = 1.12-1.65, P = 0.002), but no effect of MDD on breakfast skipping was observed (β per doubling odds of MDD =-0.001, 95%CI=-0.024 to 0.023, P = 0.957). After adjusting for multiple comparisons, the MR analysis provided little evidence for an association between breakfast skipping and the abundance of any gut microbes (PFDR>0.05). Among the 21 gut microbes with IVs available, only the abundance of Class Actinobacteria was causally associated with a reduced risk of MDD (OR = 0.85, 95%CI = 0.75-0.97, PFDR=0.015).

Our findings demonstrated that breakfast skipping was associated with an increased risk of MDD, but provided little evidence supporting the role of the abundance of gut microbes in it. Further efforts with a large sample size are warranted to clarify the findings.

Substance Use Disorders (SUDs) manifest as persistent drug-seeking behavior despite adverse consequences, with Alcohol Use Disorder (AUD) and Opioid Use Disorder (OUD) representing prevalent forms associated with significant mortality rates and economic burdens. The co-occurrence of AUD and OUD is common, necessitating a deeper comprehension of their intricate interactions. While the causal link between these disorders remains elusive, shared genetic factors are hypothesized. Leveraging public datasets, we employed genomic and transcriptomic analyses to explore conserved and distinct molecular pathways within the dorsolateral prefrontal cortex associated with AUD and OUD. Our findings unveil modest transcriptomic overlap at the gene level between the two disorders but substantial convergence on shared biological pathways. Notably, these pathways predominantly involve inflammatory processes, synaptic plasticity, and key intracellular signaling regulators. Integration of transcriptomic data with the latest genome-wide association studies (GWAS) for problematic alcohol use (PAU) and OUD not only corroborated our transcriptomic findings but also confirmed the limited shared heritability between the disorders. Overall, our study indicates that while alcohol and opioids induce diverse transcriptional alterations at the gene level, they converge on select biological pathways, offering promising avenues for novel therapeutic targets aimed at addressing both disorders simultaneously.

In this study, we mainly evaluated the associations of borderline personality disorder (BPD), neuroticism, and childhood trauma with the self-rated and clinician-rated overall functional impairment levels of adult euthymic patients with bipolar disorder-1 (BD-1). In addition, we compared patient and healthy control groups regarding the levels of of childhood trauma, neuroticism, BPD and functional impairment.

In total, 90 euthymic BD-1 patients and 90 healthy controls were enrolled. The Childhood Trauma Questionnaire-Short Form, the neuroticism subscale of the Eysenck Personality Questionnaire Revised-Abbreviated Form, the Borderline Personality Questionnaire, the Functioning Assessment Short Test, and the Sheehan Disability Scale were administered to the participants.

The study revealed that the levels of BPD, neuroticism, emotional abuse, physical abuse, global childhood trauma, self-rated overall functional impairment, all the subdomains of self-rated functional impairment, clinician-rated overall functional impairment, and all the subdomains of clinician-rated functional impairment (except leisure time) were significantly higher in the patients than those in the healthy controls (p < 0.05). Clinician-rated functional impairment levels were significantly correlated with levels of BPD (r = 0.555, p<0.001), neuroticism (r = 0.429, p < 0.001), global childhood trauma (r = 0.391, p <0.001), and all subtypes of childhood trauma except sexual abuse. Self-rated functional impairment levels were significantly correlated with levels of neuroticism (r= 0.289, p = 0.006), physical neglect (r = 0.213, p = 0.044), and BPD (r = 0.557, p < 0.001). In the regression analyses, the self-rated overall functional impairment levels were only significantly associated with the BPD feature levels (β = 0.319, p < 0.001) and the clinician-rated overall functional impairment levels were only significantly associated with the BPD feature levels (β = 0.518, p < 0.001).

The present study's findings suggest that BPD features should be addressed in psychosocial interventions aimed at ameliorating functional impairment in patients with BD-1. Only BPD features were associated with self-rated and clinician-rated overall functional impairment levels in the regression analyses in the BD-1 patients. Performing self-rated and clinician-rated functional impairment assessments in the same clinical trial may give rise to relevant findings in the future.

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity patterns of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD).

A latent class analysis (LCA) was performed on 31,197 individuals (average age 42±11 years; 49% females) from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic burden of psychiatric and behavioral traits and epigenome-wide changes in three population groups.

An LCA identified four latent classes related to SD comorbidities: AD+TD, CoD+TD, AD+CoD+OD+TD (i.e., polysubstance use, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD+TD, AD+TD, and PSU latent classes. AD+TD latent class was also associated with CpG sites located on ARID1B , NOTCH1 , SERTAD4, and SIN3B , while additional epigenome-wide significant associations with CoD+TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1 . We also observed shared polygenic score (PGS) associations for PSU, AD+TD, and CoD+TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD+TD-latent class (bipolar disorder-PGS).

We identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

To investigate the relationship and potential causality between biological ageing and periodontitis.

We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis.

We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration.

Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

Little is known about how non-suicidal and suicidal self-injury are differentially genetically related to psychopathology and related measures. This research was conducted using the UK Biobank Resource, in participants of European ancestry (N = 2320 non-suicidal self-injury [NSSI] only; N = 2648 suicide attempt; 69.18% female). We compared polygenic scores (PGS) for psychopathology and other relevant measures within self-injuring individuals. Logistic regressions and likelihood ratio tests (LRT) were used to identify PGS that were differentially associated with these outcomes. In a multivariable model, PGS for anorexia nervosa (odds ratio [OR] = 1.07; 95% confidence intervals [CI] 1.01; 1.15) and suicidal behavior (OR = 1.06; 95% CI 1.00; 1.12) both differentiated between NSSI and suicide attempt, while the PGS for other phenotypes did not. The LRT between the multivariable and base models was significant (Chi square = 11.38, df = 2, p = 0.003), and the multivariable model explained a larger proportion of variance (Nagelkerke's pseudo-R2 = 0.028 vs. 0.025). While NSSI and suicidal behavior are similarly genetically related to a range of mental health and related outcomes, genetic liability to anorexia nervosa and suicidal behavior is higher among those reporting a suicide attempt than those reporting NSSI-only. Further elucidation of these distinctions is necessary, which will require a nuanced assessment of suicidal versus non-suicidal self-injury in large samples.

Microbes have inhabited the earth for hundreds of millions of years longer than humans. The microbiota-gut-brain axis (MGBA) represents a bidirectional communication pathway. These communications occur between the central nervous system (CNS), the enteric nervous system (ENS), and the emotional and cognitive centres of the brain. The field of research on the gut-brain axis has grown significantly during the past two decades. Signalling occurs between the gut microbiota and the brain through the neural, endocrine, immune, and humoral pathways. A substantial body of evidence indicates that the MGBA plays a pivotal role in various neurological diseases. These include Alzheimer's disease (AD), autism spectrum disorder (ASD), Rett syndrome, attention deficit hyperactivity disorder (ADHD), non-Alzheimer's neurodegeneration and dementias, fronto-temporal lobe dementia (FTLD), Wilson-Konovalov disease (WD), multisystem atrophy (MSA), Huntington's chorea (HC), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), temporal lobe epilepsy (TLE), depression, and schizophrenia (SCZ). Furthermore, the bidirectional correlation between therapeutics and the gut-brain axis will be discussed. Conversely, the mood of delivery, exercise, psychotropic agents, stress, and neurologic drugs can influence the MGBA. By understanding the MGBA, it may be possible to facilitate research into microbial-based interventions and therapeutic strategies for neurological diseases.

Non-coding variants discovered by genome-wide association studies (GWAS) are enriched in regulatory elements harboring transcription factor (TF) binding motifs, strongly suggesting a connection between disease association and the disruption of cis-regulatory sequences. Occupancy of a TF inside a region of open chromatin can be detected in ATAC-seq where bound TFs block the transposase Tn5, leaving a pattern of relatively depleted Tn5 insertions known as a "footprint". Here, we sought to identify variants associated with TF-binding, or "footprint quantitative trait loci" (fpQTLs) in ATAC-seq data generated from 170 human liver samples. We used computational tools to scan the ATAC-seq reads to quantify TF binding likelihood as "footprint scores" at variants derived from whole genome sequencing generated in the same samples. We tested for association between genotype and footprint score and observed 693 fpQTLs associated with footprint-inferred TF binding (FDR < 5%). Given that Tn5 insertion sites are measured with base-pair resolution, we show that fpQTLs can aid GWAS and QTL fine-mapping by precisely pinpointing TF activity within broad trait-associated loci where the underlying causal variant is unknown. Liver fpQTLs were strongly enriched across ChIP-seq peaks, liver expression QTLs (eQTLs), and liver-related GWAS loci, and their inferred effect on TF binding was concordant with their effect on underlying sequence motifs in 80% of cases. We conclude that fpQTLs can reveal causal GWAS variants, define the role of TF binding site disruption in disease and provide functional insights into non-coding variants, ultimately informing novel treatments for common diseases.

Obesity is linked to a variety of psychosocial and behavioral outcomes but the causalities remain unclear yet. Determining the causalities and distinguishing between the separate effects of childhood and adult obesity is critical to develop more targeted strategies to prevent adverse outcomes.

With single nucleotide polymorphisms (SNPs) used as genetic variables, we employed univariable Mendelian randomization (UVMR) to explore the causalities between childhood and adult body mass index (BMI) and socioeconomic status, psychological status, and substance use. Genetic data for childhood and adult BMI came respectively from 47,541 children aged 10 years and 339,224 adult participants. The outcome data were obtained from corresponding consortia. The direct impact of childhood BMI and adult BMI was then examined using a multivariable MR (MVMR).

UVMR found that higher childhood BMI was linked causally to lower household income (β = -0.06, 95 % CI = -0.08 ∼ -0.03, P = 4.86 × 10-5), decreased subjective well-being (β = -0.07, 95 % CI = -0.12 ∼ -0.03, P = 1.74 × 10-3), and an increased tendency of smoking regularly (OR = 1.12, 95 % CI = 1.04-1.20, P = 1.52 × 10-3). Similar results were observed in adult BMI. MVMR further revealed that after adjusting with adult BMI, childhood BMI remained an isolated impact on household income. The impacts of adult BMI on the outcomes were diminished when adjusting with childhood BMI.

The findings indicate the impacts of childhood obesity on subjective well-being and smoking initiation are a result of higher BMI sustaining into adulthood, whereas the effect on household income is attributed to a lasting impact of obesity in early life. The results would help facilitate more targeted strategies for obesity management to prevent adverse outcomes.

Creativity is one defining characteristic of human species. There have been mixed findings on how creativity relates to well-being, and little is known about its relationship with career success. We conduct a large-scale genome-wide association study to examine the genetic architecture of occupational creativity, and its genetic correlations with well-being and career success. The SNP-h2 estimates range from 0.08 (for managerial creativity) to 0.22 (for artistic creativity). We record positive genetic correlations between occupational creativity with autism, and positive traits and well-being variables (e.g., physical height, and low levels of neuroticism, BMI, and non-cancer illness). While creativity share positive genetic overlaps with indicators of high career success (i.e., income, occupational status, and job satisfaction), it also has a positive genetic correlation with age at first birth and a negative genetic correlation with number of children, indicating creativity-related genes may reduce reproductive success.